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Measuring Knightian Uncertainty

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Abstract

Uncertainty shapes the trajectory of business cycles and remains a central research topic in Macroeconomics. When studying the impact of uncertainty on the economy, economists use different uncertainty measures. While all indicators approximate uncertainty along some certain dimension, none of the indicators directly captures Knightian Uncertainty. According to Knight, uncertainty represents a situation in which it is no longer possible to form expectations about the future. In this study, we propose a method to directly measure Knightian Uncertainty. Our approach relies on firm-level data and measures the share of firms that are not able to formalize expectations about their future demand. We construct the Knightian Uncertainty indicator for Switzerland and show that the indicator is able to identify times of high uncertainty and detects uncertainty shocks well. We further evaluate the indicator by comparing it to established uncertainty measures. We find that most other indicators are weakly, but statistically significantly correlated with Knightian Uncertainty.

Suggested Citation

  • David Iselin & Andreas Dibiasi, 2019. "Measuring Knightian Uncertainty," KOF Working papers 19-456, KOF Swiss Economic Institute, ETH Zurich.
  • Handle: RePEc:kof:wpskof:19-456
    DOI: 10.3929/ethz-b-000341984
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    Cited by:

    1. Beckmann, Joscha & Kerkemeier, Marco & Kruse-Becher, Robinson, 2025. "Regime-specific exchange rate predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 176(C).
    2. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    3. Eduard Ary Binsar Naibaho & Farah Margaretha Leon & Bahtiar Usman, 2025. "The Effect of Conservatism, Slack, Managerial Ability, and Uncertainty on Company Financial Performance," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 15(1), pages 1-3.
    4. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    5. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    6. Pooja Thakur-Wernz & Helena Barnard & Marianne Matthee, 2024. "Knightian uncertain violence and the challenge of FDI-assisted development: policy recommendations where civilian lives are at risk," Journal of International Business Policy, Palgrave Macmillan, vol. 7(3), pages 356-390, September.
    7. Qingyuan Li & Edward L. Maydew & Richard H. Willis & Li Xu, 2022. "Corporate tax behavior and political uncertainty: Evidence from national elections around the world," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(9-10), pages 1605-1641, October.
    8. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    9. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    10. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    11. Shamugia, Egnate, 2025. "Rule of law and economic performance: A meta-regression analysis," European Journal of Political Economy, Elsevier, vol. 87(C).

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    Keywords

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    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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